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Snowflake NAS-C01 Exam Syllabus Topics:

Section	Weight	Objectives
Snowflake Native App Framework Overview	20%	- Understand Snowflake architecture, features, tools, and best practices 1. Data sharing and protection mechanisms 2. Account security and access management 3. Cloud-based computing and storage concepts
Snowflake Native Applications Design and Creation	35%	- Apply Snowflake best practices while building native application workloads 1. Design scalable applications 2. Build, distribute, and monetize apps in Snowflake - Create and manage billing events and cost monitoring techniques 1. Formulate Snowflake native application workflows and procedures
Snowflake Native Applications Deployment	25%	- Build, version, and release native applications 1. Use data sharing for app interoperability 2. Use Snowflake's marketplace
Snowflake Native Applications Installation and Testing	20%	- Install and test native applications 1. Validate application functionality and performance

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Snowflake SnowPro Specialty - Native Apps Sample Questions (Q255-Q260):

NEW QUESTION # 255
Consider a Snowflake Native App that dynamically creates tables within the consumer's account using stored procedures. The application role is 'APP ROLE. After installation, the application needs to automatically grant 'SELECT privilege on all newly created tables in a specific schema CAPP DATA SCHEMA) to a consumer-defined role (CONSUMER ROLE). Which of the following approaches is the most secure and efficient way to achieve this? Assume the application cannot know the names of tables in advance.

A. Include code in the stored procedure that creates the table to immediately grant SELECT privilege to CONSUMER_ROLE.
B. Use a task that runs periodically to discover new tables and grant SELECT privilege to CONSUMER_ROLE.
C. Manually create tables outside of the application and grant the privileges.
D. Grant future grants on the schema for 'SELECT privilege to the 'CONSUMER_ROLE when tables are created.
E. Grant OWNERSHIP on to the APP_ROLE with the GRANT OPTION, then have the application create the tables. The CONSUMER ROLE will then have implicit access.

Answer: D

Explanation:
Future grants are designed for this purpose: to automatically grant privileges on objects created in the future. Options A and B are less efficient and scalable. Option C is overly permissive, granting ownership and the ability to grant further privileges, which is a security risk. Manual creation defeats the purpose of automation.

NEW QUESTION # 256
A Snowflake Native App provider is using a Snowpark Python UDF to process data before writing it to an event table for consumption by consumer applications. The UDF fails intermittently with a 'Java heap space' error. Which of the following strategies are MOST effective in mitigating this error?

A. Optimize the Python UDF code to use more memory-efficient data structures and algorithms, reducing overall memory consumption.
B. Increase the warehouse size used by the consumer application instance, as this controls the memory available to the UDF during event processing.
C. Configure the event table function to use a larger warehouse size using the EXECUTE AS OWNER clause.
D. Implement batch processing within the UDF to process data in smaller chunks, reducing the memory footprint at any given time.
E. Switch to a Java UDF instead of a Python UDF, as Java UDFs inherently have better memory management in Snowflake.

Answer: A,D

Explanation:
B and D are correct. B: Batch processing avoids loading the entire dataset into memory at once. D: Optimizing the code to be memory-efficient directly addresses the root cause. A is incorrect as warehouse size for the consumer application is not the controling factor for UDF event processing. C is incorrect because the warehouse size of the provider application instance controls UDF size, not consumer warehouse size. E is incorrect because switching the UDF language doesn't fundamentally solve the memory problem if the underlying code is still inefficient.

NEW QUESTION # 257
You are developing a Snowflake Native Application that relies on external functions (UDFs/UDTFs) for data processing. A new version of your application includes significant changes to these external functions, potentially affecting existing consumer data and queries. How should you manage the upgrade process to minimize disruption and ensure data integrity in consumer accounts? Assume consumers rely on your function names in their queries. Which of the following approach is MOST suitable?

A. Rename all the external functions in the new version and instruct consumers to update their queries accordingly after the upgrade.
B. Use release directives to direct users to an intermediate version that provides a compatibility layer for the external function changes. This layer translates calls to the old function names into calls to the new functions, allowing for a phased transition.
C. Create new versions of the external functions with different names while maintaining the old functions in the new version. Consumers can then migrate to the new functions at their own pace. Use release directives to route new users to new functions.
D. Develop wrapper functions in the new version that call the original external functions with the new logic applied. Consumers can then gradually migrate to the wrapper functions without immediately changing their queries.
E. Update the external functions in place with the new logic. Snowflake's versioning will automatically handle any compatibility issues for existing queries.

Answer: B

Explanation:
Option E is the MOST suitable approach. Using release directives to direct users to an intermediate version with a compatibility layer provides a smooth transition. This allows consumers to continue using their existing queries while the compatibility layer translates the calls to the updated external functions. It minimizes disruption and allows consumers to migrate at their own pace. Option A will cause immediate breakage for consumers. Option B is viable and recommended for consumers to migrate to new functions with no compatibility layers. Option C assumes a level of compatibility that may not exist. Option D might work, but it requires all the consumers to gradually migrated and update their functions calls.

NEW QUESTION # 258
You are managing the release of a new version (v2.0) of your Snowflake Native Application that introduces significant schema changes to shared tables accessed by consumer accounts. To minimize disruption during the upgrade, you want to implement a phased rollout while ensuring backward compatibility for consumers who haven't yet upgraded. Which of the following strategies would allow you to achieve this goal effectively? (Select TWO)

A. Create views on top of the new schema in v2.0 that emulate the old schema from vl .0. Grant consumers 'USAGE' on these views until they upgrade.
B. Use dynamic SQL within stored procedures to conditionally access either the old or new schema based on the consumer's account ID, identified through a custom configuration table.
C. Create separate versions of the shared tables for vl .0 and v2.0, using views to present a unified interface. Grant consumer 'USAGE on view after upgrading.
D. Publish v2.0 without any schema changes and rely on consumers to manually migrate their data to new tables after upgrading.
E. Implement API versioning within your application code and provide compatibility layers to handle requests from consumers running older versions.

Answer: A,E

Explanation:
Options A and D are both viable strategies. Creating views on top of the new schema that emulate the old schema provides backward compatibility by maintaining the expected data structure for consumers who have not yet upgraded. Implementing API versioning within the application code allows you to handle requests from consumers running older versions, ensuring that their existing integrations continue to function. Option B introduces unnecessary complexity and performance overhead with dynamic SQL. Option C relies on manual data migration by consumers, which is prone to errors and delays. Option E doubles the storage requirements by creating separate table copies.

NEW QUESTION # 259
A developer is creating a Snowsight dashboard to monitor the performance of a Snowflake Native App. They want to display a real-time graph of the number of API calls made to the app per minute. The app logs each API call to a Snowflake table named 'APP LOGS' with a timestamp column named 'CALL TIMESTAMP'. Which of the following SQL queries, when used within a Snowsight chart, would MOST accurately achieve this?

Answer: C

Explanation:

NEW QUESTION # 260
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